Opening AI for Language Learning
Aimed at language educators seeking clarity, practical insights, and critical reflections in the rapidly changing AI landscape, the Opening AI for Language Learning (OAILL) podcast explores the evolving intersection of linguistics, pedagogy, and AI in language teaching and learning. Initiated by the Language and Applied Research Center at San Diego State University (SDSU-LARC), it features hosts Mat Schulze, Professor of German and Director of SDSU-LARC, and Phil Hubbard, Senior Lecturer Emeritus at the Stanford University Language Center, longtime colleagues with decades of experience in technology for language education. In place of the all-too-common hype surrounding AI, they offer conversations in which they and occasional guests share their research and practice-informed perspectives, commentaries on others’ work, and their own professional and personal AI experiences. We are grateful for the support for Opening AI for Language Learning by the Language and Applied Research Center at San Diego State University and the Southern Area International Languages Network – SAILN – which is part of the California World Languages Project. Our producer and editor is Chris Brown. Mari Ocando Finol is the production coordinator of OAILL. Live conversations are moderated and the podcast is promoted by Shahnaz Ahmadeian. And remember: Artificial intelligence is no substitute for natural ignorance. Episodes drop on Tuesday every 2 weeks. Links: Phil Hubbard: https://web.stanford.edu/~efs/phil/ Mat Schulze: https://pantarhei.press/mat/ The PantaRhei.press blog about OAILL: https://pantarhei.press/oaill/ The SAILN website about OAILL: https://larc.sdsu.edu/oaill/
Episodes
Learning about GenAI? Mat and Phil talk about the first four (of ten) knowledge areas and skills language teachers should aim to have now: prompting, ethics, chatbots, and translation. Combining practical examples with theoretical insights, they discuss these knowledge areas and skills in more detail than they could give in their paper: AI and the future of language teaching: Motivating Sustained Integrated Professional Development...
What is a large language model (LLM), actually? How do these systems work? Why can they feel like human conversation partners, and why is that perception misleading? Mat and Phil open the podcast by answering these questions, and discussing the key implications for language teaching and learning.
In this episode:
- Phil Hubbard: https://web.stanford.edu/~efs/phil/
- Mat Schulze: https://PantaRhei.press/mat
- Emily Bender: https://faculty...
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